def plot_mangled_SED(x, y, key, inst):
p = pygplot.Plot(device='14/XS',
font=1.5,
fsize=2,
xlabel='Wavelength (Angstroms)',
ylabel='Flux')
band = inst.filter
self = inst.inst
id = argmin(power(x - self.data[band].t, 2) + power(y - self.ks[band], 2))
day = int(self.data[band].t[id])
wave, flux = kcorr.get_SED(day, version='H3')
p.line(wave, flux, label='Original SED')
if band in self.ks_mopts:
man_flux = mangle_spectrum.apply_mangle(wave, flux,
**self.ks_mopts[band][id])
p.line(wave, man_flux, label='Mangled SED', color='007700')
f1 = fset[band]
f2 = fset[self.restbands[band]]
p.line(f1.wave, f1.resp / f1.resp.max() * flux.max(), color='red')
p.line(f2.wave * (1 + self.z),
f2.resp / f2.resp.max() * flux.max(),
color='blue')
p.legend(fsize=1.5)
p.xrange = [fset[band].wave.min() * 0.9, fset[band].wave.max() * 1.1]
p.plot()
p.close()
def Rv_to_R(f1, f2, f3, Rv, EBV=0.01, day=0, redlaw='ccm',
strict_ccm=0, version='H3'):
'''Convert from R_V and optionally EBV to an observed R through
filter f1, corrected by f2-f3 color. You can choose which day
the SN SED should be (default day 0, max). You can also specify
which reddening law to use: redlaw='ccm' for Cardelli et al., or
redlaw='fm' for Fitzpatric and Malla (1999), If redlaw='ccm', you
can specify whether we should use the strict CCM relation (default no).
Finally, you an choose which SED sequence to use: 'H', 'H3', or '91bg'
(default H3).'''
# get the SNIa SED
wave,flux = kcorr.get_SED(day, version=version)
# Redden according to CCM (plus improvements if strict_ccm=0)
rflux,a,b = deredden.unred(wave, flux, -EBV, Rv, redlaw=redlaw,
strict_ccm=strict_ccm)
# compute synthetic magnitudes of original and reddened filter
m1 = fset[f1].synth_mag(wave, flux)
m1_red = fset[f1].synth_mag(wave, rflux)
m2 = fset[f2].synth_mag(wave, flux)
m2_red = fset[f2].synth_mag(wave, rflux)
m3 = fset[f3].synth_mag(wave, flux)
m3_red = fset[f3].synth_mag(wave, rflux)
# Compute extinctions
A1 = m1 - m1_red; A2 = m2 - m2_red; A3 = m3 - m3_red
# Return reddening law R
return(A1/(A2 - A3))
def advance_day(x, y, key, p):
'''A call-back function used by plot_filters() to chnage the eqpoch of the
SNIa SED plotted in the background.'''
if key == 'd':
if p.current_day < 70:
p.current_day += 1
p.title = 'Filter responses + %s SED (day %d)' % (p.version,
p.current_day)
p.sed_line.x,p.sed_line.y = kcorr.get_SED(p.current_day, p.version)
p.sed_line.y = p.sed_line.y/maximum.reduce(p.sed_line.y)
p.sed_line.x = p.sed_line.x*(1+p.z)
if key == 'D':
if p.current_day > -19:
p.current_day -= 1
p.title = 'Filter responses + %s SED (day %d)' % (p.version,
p.current_day)
p.sed_line.x,p.sed_line.y = kcorr.get_SED(p.current_day, p.version)
p.sed_line.y = p.sed_line.y/maximum.reduce(p.sed_line.y)
p.sed_line.x = p.sed_line.x*(1+p.z)
def advance_day(x, y, key, p):
'''A call-back function used by plot_filters() to chnage the eqpoch of the
SNIa SED plotted in the background.'''
if key == 'd':
if p.current_day < 70:
p.current_day += 1
p.title = 'Filter responses + %s SED (day %d)' % (p.version,
p.current_day)
p.sed_line.x, p.sed_line.y = kcorr.get_SED(p.current_day,
p.version)
p.sed_line.y = p.sed_line.y / maximum.reduce(p.sed_line.y)
p.sed_line.x = p.sed_line.x * (1 + p.z)
if key == 'D':
if p.current_day > -19:
p.current_day -= 1
p.title = 'Filter responses + %s SED (day %d)' % (p.version,
p.current_day)
p.sed_line.x, p.sed_line.y = kcorr.get_SED(p.current_day,
p.version)
p.sed_line.y = p.sed_line.y / maximum.reduce(p.sed_line.y)
p.sed_line.x = p.sed_line.x * (1 + p.z)
def plot_mangled_SED(event):
f = pyplot.figure(num=113)
f.clear()
ax = f.add_subplot(111)
ax.set_xlabel('Wavelength (Angstroms)')
ax.set_ylabel('Flux')
band = event.inaxes.filt
self = event.inaxes.inst
x = event.xdata
y = event.ydata
id = argmin(power(x - self.data[band].t, 2) + power(y - self.ks[band], 2))
day = int(self.data[band].t[id])
wave, flux = kcorr.get_SED(day, version='H3')
ax.plot(wave, flux, label='Original SED', color='black')
if band in self.ks_mopts:
if 'state' in self.ks_mopts[band][id]:
man_flux = mangle_spectrum.apply_mangle(
wave, flux, **self.ks_mopts[band][id])[0]
else:
args = {}
args['state'] = dict(ave_waves=self.ks_mopts[band][id]['sw'])
args['pars'] = self.ks_mopts[band][id]['sf']
man_flux = mangle_spectrum.apply_mangle(wave,
flux,
init=False,
**args)[0]
else:
man_flux = flux
ax.plot(wave, man_flux, label='Mangled SED', color='darkgreen')
ax.plot(wave, man_flux / flux * ax.get_ylim()[1], color='orange')
f1 = fset[band]
f2 = fset[self.restbands[band]]
ax.plot(f1.wave, f1.resp / f1.resp.max() * ax.get_ylim()[1], color='red')
ax.plot(f2.wave * (1 + self.z),
f2.resp / f2.resp.max() * ax.get_ylim()[1],
color='blue')
#wmax = max(f1.wave.max(), f2.wave.max()*(1+self.z))
#wmin = max(f1.wave.min(), f2.wave.min()*(1+self.z))
#dw = wmax - wmin
#wmax += dw*0.05
#wmin -= dw*0.05
ax.legend()
#ax.set_xlim(wmin,wmax)
pyplot.tight_layout()
f.canvas.draw()
def plot_color(self, f1, f2, epoch=True, deredden=True, interp=False,
dokcorr=False, outfile=None, clear=True):
'''Plot the color ([f1]-[f2]) evolution curve for the SN. If [epoch]
is True and Bmax is defined, plot relative to T(Bmax). If [deredden]
is True, remove MW reddening. Specify [outfile] to save to file.'''
p = pyplot.figure(114)
if clear: p.clear()
ax = p.add_subplot(111)
ax.set_xlabel('JD - JD(Bmax)')
ax.set_ylabel('%s-%s' % (f1,f2))
MJD,BV,eBV,flag = self.get_color(f1, f2, interp=interp, use_model=0,
dokcorr=dokcorr)
if epoch:
if self.Tmax:
t0 = self.Tmax
elif 'B' in self.data and getattr(self.data['B'],'Tmax',None) is not None:
t0 = self.B.Tmax
else:
t0 = 0
else:
t0 = 0
if deredden:
Ia_w,Ia_f = kcorr.get_SED(0, 'H3')
R1 = fset[f1].R(wave=Ia_w, flux=Ia_f, Rv=3.1)
R2 = fset[f2].R(wave=Ia_w, flux=Ia_f, Rv=3.1)
BV = BV - (R1-R2)*self.EBVgal
eBV = sqrt(power(eBV,2) + (R1-R2)**2*0.1**2*self.EBVgal**2)
bids = equal(flag, 0)
rids = equal(flag, 1)
ax.errorbar(MJD[bids]-t0, BV[bids], yerr=eBV[bids], fmt='o', capsize=0,
color='black', label='obs')
if sometrue(rids):
ax.errorbar(MJD[rids]-t0, BV[rids], yerr=eBV[rids], fmt='o', capsize=0,
color='red', mfc='red', label='inter')
ax.legend(prop={'size':12})
pyplot.tight_layout()
pyplot.draw()
#p.canvas.draw()
if outfile is not None:
p.savefig(outfile)
return p
def plot_color(self, f1, f2, epoch=True, deredden=True, interp=False,
dokcorr=False, outfile=None, clear=True):
'''Plot the color ([f1]-[f2]) evolution curve for the SN. If [epoch]
is True and Bmax is defined, plot relative to T(Bmax). If [deredden]
is True, remove MW reddening. Specify [outfile] to save to file.'''
p = pyplot.figure(114)
if clear: p.clear()
ax = p.add_subplot(111)
ax.set_xlabel('JD - JD(Bmax)')
ax.set_ylabel('%s-%s' % (f1,f2))
MJD,BV,eBV,flag = self.get_color(f1, f2, interp=interp, use_model=0,
dokcorr=dokcorr)
if epoch:
if self.Tmax:
t0 = self.Tmax
elif 'B' in self.data and getattr(self.data['B'],'Tmax',None) is not None:
t0 = self.B.Tmax
else:
t0 = 0
else:
t0 = 0
if deredden:
Ia_w,Ia_f = kcorr.get_SED(0, 'H3')
R1 = fset[f1].R(wave=Ia_w, flux=Ia_f, Rv=3.1)
R2 = fset[f2].R(wave=Ia_w, flux=Ia_f, Rv=3.1)
BV = BV - (R1-R2)*self.EBVgal
eBV = sqrt(power(eBV,2) + (R1-R2)**2*0.1**2*self.EBVgal**2)
bids = equal(flag, 0)
rids = equal(flag, 1)
ax.errorbar(MJD[bids]-t0, BV[bids], yerr=eBV[bids], fmt='o', capsize=0,
color='black', label='obs')
if sometrue(rids):
ax.errorbar(MJD[rids]-t0, BV[rids], yerr=eBV[rids], fmt='o', capsize=0,
color='red', mfc='red', label='inter')
ax.legend(prop={'size':12})
pyplot.tight_layout()
pyplot.draw()
#p.canvas.draw()
if outfile is not None:
p.savefig(outfile)
return p
def Rv_to_R(f1,
f2,
f3,
Rv,
EBV=0.01,
day=0,
redlaw='ccm',
strict_ccm=0,
version='H3'):
'''Convert from R_V and optionally EBV to an observed R through
filter f1, corrected by f2-f3 color. You can choose which day
the SN SED should be (default day 0, max). You can also specify
which reddening law to use: redlaw='ccm' for Cardelli et al., or
redlaw='fm' for Fitzpatric and Malla (1999), If redlaw='ccm', you
can specify whether we should use the strict CCM relation (default no).
Finally, you an choose which SED sequence to use: 'H', 'H3', or '91bg'
(default H3).'''
# get the SNIa SED
wave, flux = kcorr.get_SED(day, version=version)
# Redden according to CCM (plus improvements if strict_ccm=0)
rflux, a, b = deredden.unred(wave,
flux,
-EBV,
Rv,
redlaw=redlaw,
strict_ccm=strict_ccm)
# compute synthetic magnitudes of original and reddened filter
m1 = fset[f1].synth_mag(wave, flux)
m1_red = fset[f1].synth_mag(wave, rflux)
m2 = fset[f2].synth_mag(wave, flux)
m2_red = fset[f2].synth_mag(wave, rflux)
m3 = fset[f3].synth_mag(wave, flux)
m3_red = fset[f3].synth_mag(wave, rflux)
# Compute extinctions
A1 = m1 - m1_red
A2 = m2 - m2_red
A3 = m3 - m3_red
# Return reddening law R
return (A1 / (A2 - A3))
def change_SED(event):
fig = event.inaxes.figure
ax = event.inaxes
if event.key == 'd':
if fig.current_day < 70:
fig.current_day += 1
ax.set_title('Filter responses + %s SED (day %d)' % \
(fig.version,fig.current_day))
elif event.key == 'D':
if fig.current_day > -19:
fig.current_day -= 1
ax.set_title('Filter responses + %s SED (day %d)' % \
(fig.version,fig.current_day))
wave,flux = kcorr.get_SED(fig.current_day, version='H3')
fig.sed_line.set_data(wave*(1+fig.z), flux/flux.max())
if fig.sed_fill is not None:
fig.sed_fill.remove()
fig.sed_fill = fig.axes[0].fill_between(wave*(1+fig.z), flux/flux.max(),
facecolor='black', alpha=0.1)
fig.canvas.draw()
def change_SED(event):
fig = event.inaxes.figure
ax = event.inaxes
if event.key == 'd':
if fig.current_day < 70:
fig.current_day += 1
ax.set_title('Filter responses + %s SED (day %d)' % \
(fig.version,fig.current_day))
elif event.key == 'D':
if fig.current_day > -19:
fig.current_day -= 1
ax.set_title('Filter responses + %s SED (day %d)' % \
(fig.version,fig.current_day))
wave,flux = kcorr.get_SED(fig.current_day, version='H3')
fig.sed_line.set_data(wave*(1+fig.z), flux/flux.max())
if fig.sed_fill is not None:
fig.sed_fill.remove()
fig.sed_fill = fig.axes[0].fill_between(wave*(1+fig.z), flux/flux.max(),
facecolor='black', alpha=0.1)
fig.canvas.draw()
def plot_filters(self, bands=None, day=0):
'''Plot the filter responses, both the observed ones and the restbands
defined in the sn instance in the rest frame of the SN. If bands is specified,
only plot those. Specify which SED to plot using day.'''
p = pygplot.Plot(xlabel='Wavelength (\A)',
ylabel='relative flux',
title='Filter responses + %s SED (day %d)' %
(self.k_version, day),
device="11/XWIN")
# first, get the SED:
sed_wav, sed_flux = kcorr.get_SED(day, self.k_version)
# normalize:
sed_flux = sed_flux / maximum.reduce(sed_flux)
p.sed_line = p.line(sed_wav * (1 + self.z), sed_flux, autorange=0)
p.current_day = day
p.version = self.k_version
p.z = self.z
# Next, for each filter, plot the response and rest band closest to it:
if bands is None: bands = list(self.data.keys())
if type(bands) is bytes:
bands = [bands]
for band in bands:
f1 = fset[band]
f2 = fset[self.restbands[band]]
maxresp = maximum.reduce(f1.resp)
max_wave = f1.wave[argmax(f1.resp)]
p.line(f1.wave, f1.resp / maxresp, color='blue')
p.label(max_wave, 1.05, band, color='blue')
maxresp = maximum.reduce(f2.resp)
max_wave = f2.wave[argmax(f2.resp)] * (1 + self.z)
p.line(f2.wave * (1 + self.z), f2.resp / maxresp, color='red')
p.label(max_wave, 1.05, self.restbands[band], color='red')
p.plot()
p.interact(bindings={'D': advance_day, 'd': advance_day})
pygplot.ppgplot.pgask(0)
p.close()
def plot_filters(self, bands=None, day=0):
'''Plot the filter responses, both the observed ones and the restbands
defined in the sn instance in the rest frame of the SN. If bands is specified,
only plot those. Specify which SED to plot using day.'''
p = pygplot.Plot(xlabel='Wavelength (\A)', ylabel='relative flux',
title='Filter responses + %s SED (day %d)' % (self.k_version,day),
device="11/XWIN")
# first, get the SED:
sed_wav,sed_flux = kcorr.get_SED(day, self.k_version)
# normalize:
sed_flux = sed_flux/maximum.reduce(sed_flux)
p.sed_line = p.line(sed_wav*(1+self.z),sed_flux, autorange=0)
p.current_day = day
p.version = self.k_version
p.z = self.z
# Next, for each filter, plot the response and rest band closest to it:
if bands is None: bands = self.data.keys()
if type(bands) is types.StringType:
bands = [bands]
for band in bands:
f1 = fset[band]
f2 = fset[self.restbands[band]]
maxresp = maximum.reduce(f1.resp)
max_wave = f1.wave[argmax(f1.resp)]
p.line(f1.wave, f1.resp/maxresp, color='blue')
p.label(max_wave,1.05, band, color='blue')
maxresp = maximum.reduce(f2.resp)
max_wave = f2.wave[argmax(f2.resp)]*(1+self.z)
p.line(f2.wave*(1+self.z), f2.resp/maxresp, color='red')
p.label(max_wave, 1.05, self.restbands[band], color='red')
p.plot()
p.interact(bindings={'D':advance_day, 'd':advance_day})
pygplot.ppgplot.pgask(0)
p.close()
def plot_mangled_SED(x, y, key, inst):
p = pygplot.Plot(device='14/XS', font=1.5, fsize=2, xlabel='Wavelength (Angstroms)',
ylabel='Flux')
band = inst.filter
self = inst.inst
id = argmin(power(x - self.data[band].t,2) + power(y - self.ks[band],2))
day = int(self.data[band].t[id])
wave,flux = kcorr.get_SED(day, version='H3')
p.line(wave,flux, label='Original SED')
if band in self.ks_mopts:
man_flux = mangle_spectrum.apply_mangle(wave,flux, **self.ks_mopts[band][id])
p.line(wave, man_flux, label='Mangled SED', color='007700')
f1 = fset[band]
f2 = fset[self.restbands[band]]
p.line(f1.wave, f1.resp/f1.resp.max()*flux.max(), color='red')
p.line(f2.wave*(1+self.z), f2.resp/f2.resp.max()*flux.max(),
color='blue')
p.legend(fsize=1.5)
p.xrange = [fset[band].wave.min()*0.9, fset[band].wave.max()*1.1]
p.plot()
p.close()
def plot_mangled_SED(event):
f = pyplot.figure(num=113)
f.clear()
ax = f.add_subplot(111)
ax.set_xlabel('Wavelength (Angstroms)')
ax.set_ylabel('Flux')
band = event.inaxes.filt
self = event.inaxes.inst
x = event.xdata; y = event.ydata
id = argmin(power(x - self.data[band].t,2) + power(y - self.ks[band],2))
day = int(self.data[band].t[id])
wave,flux = kcorr.get_SED(day, version='H3')
ax.plot(wave,flux, label='Original SED', color='black')
if band in self.ks_mopts:
man_flux = mangle_spectrum.apply_mangle(wave,flux, **self.ks_mopts[band][id])[0]
ax.plot(wave, man_flux, label='Mangled SED', color='darkgreen')
ax.plot(wave, man_flux/flux*ax.get_ylim()[1], color='orange')
f1 = fset[band]
f2 = fset[self.restbands[band]]
ax.plot(f1.wave, f1.resp/f1.resp.max()*ax.get_ylim()[1], color='red')
ax.plot(f2.wave*(1+self.z), f2.resp/f2.resp.max()*ax.get_ylim()[1],
color='blue')
#wmax = max(f1.wave.max(), f2.wave.max()*(1+self.z))
#wmin = max(f1.wave.min(), f2.wave.min()*(1+self.z))
#dw = wmax - wmin
#wmax += dw*0.05
#wmin -= dw*0.05
ax.legend()
#ax.set_xlim(wmin,wmax)
pyplot.tight_layout()
f.canvas.draw()
def plot_filters(self, bands=None, day=0, fill=0, outfile=None):
'''Plot the filt responses, both the observed ones and the restbands
defined in the sn instance in the rest frame of the SN. If bands is specified,
only plot those. Specify which SED to plot using day.'''
p = pyplot.figure(112)
p.clear()
ax = p.add_subplot(111,
title='Filter responses + %s SED (day %d)' %
(self.k_version, day),
xlabel='Wavelength ($\AA$)',
ylabel='Relative Flux',
autoscale_on=False,
ylim=(0, 1.1))
p.current_day = day
p.version = self.k_version
p.z = self.z
# Next, for each filt, plot the response and rest band closest to it:
if bands is None: bands = list(self.data.keys())
if type(bands) is bytes:
bands = [bands]
minw = 1e12
maxw = -1
for band in bands:
f1 = fset[band]
f2 = fset[self.restbands[band]]
minw = min(minw, f1.wave[0], f2.wave[0])
maxw = max(maxw, f1.wave[-1], f2.wave[-1])
maxresp = f1.resp.max()
max_wave = f1.wave[argmax(f1.resp)]
ax.plot(f1.wave, f1.resp / maxresp, '-', color='blue')
if fill:
ax.fill_between(f1.wave,
f1.resp / maxresp,
facecolor='blue',
alpha=0.1)
ax.annotate(band, (max_wave, 1.05),
color='blue',
horizontalalignment='center',
verticalalignment='center')
maxresp = maximum.reduce(f2.resp)
max_wave = f2.wave[argmax(f2.resp)] * (1 + self.z)
ax.plot(f2.wave * (1 + self.z), f2.resp / maxresp, '-', color='red')
if fill:
ax.fill_between(f2.wave * (1 + self.z),
f2.resp / maxresp,
facecolor='red',
alpha=0.1)
ax.annotate(self.restbands[band], (max_wave, 1.05),
color='red',
horizontalalignment='center',
verticalalignment='center')
# first, get the SED:
sed_wav, sed_flux = kcorr.get_SED(day, self.k_version)
# normalize:
sed_flux = sed_flux / sed_flux.max()
p.sed_line = ax.plot(sed_wav * (1 + self.z),
sed_flux,
scalex=False,
color='black')[0]
if fill:
p.sed_fill = ax.fill_between(sed_wav * (1 + self.z),
sed_flux,
facecolor='black',
alpha=0.1)
else:
p.sed_fill = None
ax.set_xbound((minw, maxw))
pyplot.tight_layout()
pyplot.draw()
p.cb = ButtonClick(p, bindings={'d': change_SED, 'D': change_SED})
p.cb.connect()
if outfile is not None:
p.savefig(outfile)
return p
def plot_filters(self, bands=None, day=0, fill=0, outfile=None):
'''Plot the filt responses, both the observed ones and the restbands
defined in the sn instance in the rest frame of the SN. If bands is specified,
only plot those. Specify which SED to plot using day.'''
p = pyplot.figure(112)
p.clear()
ax = p.add_subplot(111,
title='Filter responses + %s SED (day %d)' % (self.k_version,day),
xlabel='Wavelength ($\AA$)', ylabel='Relative Flux',
autoscale_on=False, ylim=(0,1.1))
p.current_day = day
p.version = self.k_version
p.z = self.z
# Next, for each filt, plot the response and rest band closest to it:
if bands is None: bands = self.data.keys()
if type(bands) is types.StringType:
bands = [bands]
minw = 1e12
maxw = -1
for band in bands:
f1 = fset[band]
f2 = fset[self.restbands[band]]
minw = min(minw, f1.wave[0], f2.wave[0])
maxw = max(maxw, f1.wave[-1], f2.wave[-1])
maxresp = f1.resp.max()
max_wave = f1.wave[argmax(f1.resp)]
ax.plot(f1.wave, f1.resp/maxresp, '-', color='blue')
if fill:
ax.fill_between(f1.wave, f1.resp/maxresp, facecolor='blue', alpha=0.1)
ax.annotate(band, (max_wave,1.05), color='blue',
horizontalalignment='center', verticalalignment='center')
maxresp = maximum.reduce(f2.resp)
max_wave = f2.wave[argmax(f2.resp)]*(1+self.z)
ax.plot(f2.wave*(1+self.z), f2.resp/maxresp, '-', color='red')
if fill:
ax.fill_between(f2.wave*(1+self.z), f2.resp/maxresp, facecolor='red', alpha=0.1)
ax.annotate(self.restbands[band], (max_wave, 1.05), color='red',
horizontalalignment='center', verticalalignment='center')
# first, get the SED:
sed_wav,sed_flux = kcorr.get_SED(day, self.k_version)
# normalize:
sed_flux = sed_flux/sed_flux.max()
p.sed_line = ax.plot(sed_wav*(1+self.z),sed_flux, scalex=False, color='black')[0]
if fill:
p.sed_fill = ax.fill_between(sed_wav*(1+self.z),sed_flux,
facecolor='black', alpha=0.1)
else:
p.sed_fill = None
ax.set_xbound((minw, maxw))
pyplot.tight_layout()
pyplot.draw()
p.cb = ButtonClick(p, bindings={'d':change_SED, 'D':change_SED})
p.cb.connect()
if outfile is not None:
p.savefig(outfile)
return p
